Your new experience awaits. Try the new design now and help us make it even better

ORIGINAL RESEARCH article

Front. Endocrinol.

Sec. Clinical Diabetes

Volume 16 - 2025 | doi: 10.3389/fendo.2025.1681689

This article is part of the Research TopicDiabetes Complications: Navigating Challenges and Unveiling New SolutionsView all 13 articles

Long-term trends and future projections of the burden of Diabetic nephropathy in China: a comprehensive analysis of GBD data from 1990 to 2036

Provisionally accepted
Yan  ZHANGYan ZHANG1,2Dong  HouDong Hou3Zihui  CHAIZihui CHAI1,2Xizi  LiXizi Li1,2Chuchu  ShanChuchu Shan1,2Yuetong  ZhaoYuetong Zhao1,2Siyuan  SongSiyuan Song1,2Ying  TanYing Tan1Jiangyi  YuJiangyi Yu1*
  • 1Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
  • 2Nanjing University of Chinese Medicine, Nanjing, China
  • 3Gansu University of Chinese Medicine, Lanzhou, China

The final, formatted version of the article will be published soon.

Background:Diabetic nephropathy (DN) is a prevalent and serious microvascular complication of diabetes that poses a significant public health challenge and negatively impacts quality of life in China.The objective of this study was to evaluate the disease burden of type 2 diabetic nephropathy in China and to predict the trend of this burden over the next 15 years. Methods:This study used the Global Burden of Disease (GBD) system to analyze trends in the disease burden of type 2 DN in China between 1990 and 2021.The study utilized prevalence, incidence, deaths, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) for DN, along with their 95% uncertainty intervals (UIs). Secondly, joinpoint Regression, age-period-cohort, and decomposition analyses were employed to estimate the contribution of epidemiological changes to the DN burden. We used the inequality slope index (SII) and concentration index to assess absolute and relative cross-country inequalities in 1990 and 2021. Furthermore, Bayesian age-period-cohort (BAPC) models were employed to predict the future burden of DN from 2022 to 2036. Results:From 1990 to 2021, the burden of DN in China continued to increase, reaching a total of 20,911,520 cases. The age-standardized prevalence rate (ASPR) was 1,053.92 per 100,000 people.The agestandardized incidence rate (ASIR) was 16.29 per 100,000 people, and the age-standardized death rate (ASDR) was 5.64 per 100,000 people. Age-standardized DALYs were 122.15 per 100,000 people.In 2021, the overall burden of DN continued to increase, with the effect of age strengthening with increasing age. The incidence rate showed a sustained upward trend. Decomposition analysis revealed that population ageing was the main cause of the increased burden of DN in China. Predictive Analysis suggests that the ASIR will continue to rise from 2022 to 2036, while the ASDR will decrease.Conclusion:DN places a significant burden on China's healthcare system, primarily due to an ageing population. The incidence rate is expected to increase over the next 15 years before declining. Given China's large population and severe ageing, implementing a tiered prevention and control strategy, strengthening health education, and promoting early, effective prevention are imperative to alleviating the disease burden in China.

Keywords: Diabetic Nephropathy (DN), Global Burden of Disease (GBD), Inequality, prediction, Joinpoint regression analysis, Age-Period-Cohort Analysis (APC)

Received: 07 Aug 2025; Accepted: 24 Sep 2025.

Copyright: © 2025 ZHANG, Hou, CHAI, Li, Shan, Zhao, Song, Tan and Yu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Jiangyi Yu, 2647377909@qq.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.